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Knowledge extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources.The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing.
File metadata, including the schema definition. The 16-byte, randomly-generated sync marker for this file. For data blocks Avro specifies two serialization encodings: [6] binary and JSON. Most applications will use the binary encoding, as it is smaller and faster. For debugging and web-based applications, the JSON encoding may sometimes be ...
The idea is that if the object (actually class) were a POJO before any annotations were added, and would return to POJO status if the annotations are removed then it can still be considered a POJO. Then the basic object remains a POJO in that it has no special characteristics (such as an implemented interface) that makes it a "Specialized Java ...
JSON Schema specifies a JSON-based format to define the structure of JSON data for validation, documentation, and interaction control. It provides a contract for the JSON data required by a given application and how that data can be modified. [29] JSON Schema is based on the concepts from XML Schema (XSD) but is JSON-based. As in XSD, the same ...
Schema.org is a reference website that publishes documentation and guidelines for using structured data mark-up on web-pages (called microdata).Its main objective is to standardize HTML tags to be used by webmasters for creating rich results (displayed as visual data or infographic tables on search engine results) about a certain topic of interest. [2]
JSON-LD is designed around the concept of a "context" to provide additional mappings from JSON to an RDF model. The context links object properties in a JSON document to concepts in an ontology. In order to map the JSON-LD syntax to RDF, JSON-LD allows values to be coerced to a specified type or to be tagged with a language.
A SHACL validation engine takes as input a graph to be validated (called data graph) and a graph containing SHACL shapes declarations (called shapes graph) and produces a validation report, also expressed as a graph. All these graphs can be represented in any Resource Description Framework (RDF) serialization formats including JSON-LD or Turtle.
[4] [5] Supporting schema evolution is a difficult problem involving complex mapping among schema versions and the tool support has been so far very limited. The recent theoretical advances on mapping composition [ 6 ] and mapping invertibility, [ 7 ] which represent the core problems underlying the schema evolution remains almost inaccessible ...